In the early days of AI, models could “see”, “read”, or “listen”—but rarely all at once. A model built for text would only understand text, and one for images would only understand images. Each modality was an island. 

But Humans don’t work this way. We are inherently multimodal thinkers—connect words, images, sounds, and experiences into a single, unified understanding. Today, with the advent of Multimodal AI, machines are beginning to do the same. It enables AI systems to process, understand, and generate content across multiple data types simultaneously—images (photos, diagrams), audio (speech, music), text (written words, documents, chat, code), and even video (motion, gestures)—as seamlessly as a human.

Why does it matter in CRM?

Traditional CRM interactions were text or form-driven—emails, tickets, call logs, structured fields. But the customer journey today is inherently complex and non-linear that go far beyond chatbots and emails. With the rise of Multimodal AI, CRM systems can unify these diverse signals into actionable intelligence—driving faster resolutions, smarter sales, and richer customer experiences.

  • Deeper Contextual Understanding: By leveraging data from multiple sources, multimodal AI systems develop a more comprehensive view of the information, leading to improved accuracy and relevance in their responses.
  • Enhanced Customer Journeys: Think virtual assistants that interpret spoken queries while also recognizing objects through the camera, or customer service bots that understand both the text and emotions in a video chat.
  • Smarter Automation: Multimodal AI can automatically extract meaningful information from images and convert it into structured text.

Multimodal AI in Siebel CRM

We are excited to announce the general availability of Multimodal AI in Siebel CRM that represents a significant step toward creating AI capabilties that can reason, understand, and interact with the world in a way that is far more akin to human cognition. With our out-of-the-box and configurable use cases, we’ve made it easier for customers to move from specialized, single-task AIs to a more holistic, human-like form of intelligence.

Let’s walk through a few examples:

  • After a call or a series of email messages, a multimodal AI can process the entire interaction, including text transcripts and any attached images, to generate a comprehensive summary.
  • A customer calling to report a problem can now do more than just describe it. They can attach an image to the service request, captured directly from a mobile device or a customer portal. A multimodal AI can use image classification to identify the product model, object detection to pinpoint the broken part, and text analysis to understand the customer’s stated problem.
  • Let’s say a salesperson uploads a customer RFP (PDF), along with previous deal notes—AI generates a draft proposal, pulling visuals, charts, and relevant product text.
  • With multimodal, a salesperson AI can capture customer meetings—process slides presented, record conversations, and extract key action items into the opportunity record.

Multimodal AI stands at the forefront of making machines more perceptive, intuitive, and capable of engaging with the world in ways closer to human understanding. We’re only scratching the surface of what multimodal AI can achieve.

To learn more about the real-world use cases of Multimodal AI in Siebel CRM, visit our documentation or contact your Oracle representative. 

Curious to see Multimodal AI in action? Register for this webinar “Empowering Decisions with AI Multimodal & GSAT Score in Siebel CRM” today. The webinar will be available for replay.